(a) Suppose that, when using grid search with cross-validation to select the parameters C and gamma of the Support Vector Machine (SVM), you have obtained these results for the accuracy of the algorithm: (As usual, the accuracy is defined as 1 minus the error rate.) Is this a suitable grid for selecting the optimal values of the two parameters? Explain why. If it is not suitable, describe at least one way of improving it.[7 marks] (b) Give an example of a grid that is too crude and thus does not allow an accurate estimate of the optimal values of the parameters C and gamma of the SVM.[7 marks] (c) Give an example of a grid that clearly does not cover the optimal values ofthe parameters C and gamma of the SVM. Briefly explain why your example achieves its goal.[7 marks]

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a suppose that when using grid search with cross validation to select

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(a) Suppose that, when using grid search with cross-validation to select the parameters C and gamma of the Support Vector Machine (SVM), you have obtained these results for the accuracy of the algorithm: (As usual, the accuracy is defined as 1 minus the error rate.) Is this a suitable grid for selecting the optimal